The Lived Fracture Experience (LiFE) study: A mixed methods qualitative study research protocol exploring the lived experiences of fracture non-union patients
Bibliographic record
Abstract
BACKGROUND: Fractures are a common and a major cause of disability and death, with up to 10% of fractures failing to heal normally. These fractures are called "fracture non-unions". Currently, debate on the impact of non-union in the medical and research communities exists. Unfortunately, this indirectly minimizes the impact of fracture non-unions, and hinders further research work which could reduce unnecessary patient suffering. In this study, we aim to explore the lived experiences of fracture non-union patients in one-on-one interviews to determine whether fracture non-union is a burden for patients, and if so, to outline the burden on patients and their close circles. METHODS: Eligible participants will include adult patients who currently have/previously (in the last 36 months) had a long bone fracture that has not healed normally. Data will be collected through in-depth face-to-face or telephone interviews, complemented by quantitative data captured using the standardized Euroqol EQ-5D-5L questionnaire. With consent, interviews will be audio-recorded and transcribed verbatim. Using NVIVO software, we will develop grouped codes and categories to describe and provide insight into the experience of fracture non-union patients. EQ-5D-5L, and EQ VAS data will be presented using a measure of central tendency and a measure of dispersion to provide insight into the overall health related quality of life for patients. ETHICS AND DISSEMINATION: The study was approved by the Health Research Authority and Health and Care Research Wales Approval (approval date: 27 March 2024; IRAS project ID: 337652). Results from this study aim to improve the information and support provided to fracture non-union patients. Findings will be disseminated to the study participants, healthcare professionals, and local commissioners through peer-reviewed articles and at academic conferences.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.046 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".